22,341 research outputs found
Distributed Stochastic Optimization of the Regularized Risk
Many machine learning algorithms minimize a regularized risk, and stochastic
optimization is widely used for this task. When working with massive data, it
is desirable to perform stochastic optimization in parallel. Unfortunately,
many existing stochastic optimization algorithms cannot be parallelized
efficiently. In this paper we show that one can rewrite the regularized risk
minimization problem as an equivalent saddle-point problem, and propose an
efficient distributed stochastic optimization (DSO) algorithm. We prove the
algorithm's rate of convergence; remarkably, our analysis shows that the
algorithm scales almost linearly with the number of processors. We also verify
with empirical evaluations that the proposed algorithm is competitive with
other parallel, general purpose stochastic and batch optimization algorithms
for regularized risk minimization
Integrated reconfigurable control and guidance based on evaluation of degraded performance
The present paper is focused on analysing an integrated reconfigurable control and guidance approach for recovering a small fixed-wing UAV from different actuator faults, which cover locked in place (stuck) and loss of effectiveness. The model of the UAV Aerosonde is used to develop a reconfigurable control system based on the control allocation technique for a variety of faults, such as locked-in-place control surfaces. It is shown through simulation that the developed technique is successful to recover the aircraft from various faults but cannot guarantee success on the planned mission. For mission scenarios where performance degradation is such that the prescribed trajectory cannot be achieved, a reconfigurable guidance system is developed, which is capable of adapting parameters such as the minimum turning radius and the look-ahead distance for obstacle avoidance, to allow the vehicle to dynamically generate a path which guides the aircraft around the no-fly zones taking into account the post-fault reduced performance. Path following is performed by means of a non-linear lateral guidance law and a collision avoidance algorithm is implemented as well. Finally, the integration of control reconfiguration and guidance adaptation is carried out to maximise probabilities of post-failure success in the mission. A methodology is developed, using an error based control allocation parameter, as a measure of performance degradation, which links both reconfiguration and guidance systems. The developed method, although approximate, is proven to be an efficient way of allocating the required degree of reconfiguration in guidance commands when an accurate prediction of the actual performance is not available
Feedback effects on the current correlations in Y-shaped conductors
We study current fluctuations in a Y-shaped conductor connected to external
leads with finite impedances. We show that, due to voltage fluctuations in the
circuit, the moments of the transferred charges cannot be obtained from simple
rescaling of the bare values already in the second moments. The
cross-correlation between the output terminals can change from negative to
positive under certain parameter regimes.Comment: 4 pages, figures attached separatel
Application of multivariate analysis in the processing of medical data
Medical data frequently represent multidimensional datasets as investigated factors and clinical and laboratory parameters coverage is huge. This research area is very important in terms of practical applications. We were given monthly lipid metabolism and hormonal status data of children (including children suffering from obesity) of Siberian region during a year. In this article some research results appear
On the Design of Secure Full-Duplex Multiuser Systems under User Grouping Method
Consider a full-duplex (FD) multiuser system where an FD base station (BS) is
designed to simultaneously serve both downlink users and uplink users in the
presence of half-duplex eavesdroppers (Eves). Our problem is to maximize the
minimum secrecy rate (SR) among all legitimate users by proposing a novel user
grouping method, where information signals at the FD-BS are accompanied with
artificial noise to degrade the Eves' channel. The SR problem has a highly
nonconcave and nonsmooth objective, subject to nonconvex constraints due to
coupling between the optimization variables. Nevertheless, we develop a
path-following low-complexity algorithm, which invokes only a simple convex
program of moderate dimensions at each iteration. We show that our
path-following algorithm guarantees convergence at least to a local optima. The
numerical results demonstrate the merit of our proposed approach compared to
existing well-known ones, i.e., conventional FD and nonorthogonal multiple
access.Comment: 6 pages, 3 figure
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